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CVPR
2010
IEEE
14 years 1 months ago
Group MRF for fMRI Activation Detection
Noise confounds present serious complications to accurate data analysis in functional magnetic resonance imaging (fMRI). Simply relying on contextual image information often resul...
Bernard Ng, Rafeef Abugharbieh, Ghassan Hamarneh
IPMI
2009
Springer
14 years 1 days ago
Discovering Sparse Functional Brain Networks Using Group Replicator Dynamics (GRD)
Functional magnetic resonance imaging (fMRI) has become increasingly used for studying functional integration of the brain. However, the large inter-subject variability in function...
Bernard Ng, Rafeef Abugharbieh, Martin J. McKeown
ICIP
1995
IEEE
14 years 8 months ago
Selection of observations in magnetic resonance spectroscopic imaging
Magnetic resonance spectroscopic imaging (MRSI) is a type of MRI in which both spatial and spectral information are gathered. Unfortunately, the time required to acquire a high-re...
Stanley J. Reeves, R. Hezar
EMMCVPR
1999
Springer
13 years 11 months ago
Markov Random Field Modelling of fMRI Data Using a Mean Field EM-algorithm
This paper considers the use of the EM-algorithm, combined with mean field theory, for parameter estimation in Markov random field models from unlabelled data. Special attention ...
Markus Svensén, Frithjof Kruggel, D. Yves v...
MICCAI
2002
Springer
14 years 8 months ago
Improved Detection Sensitivity in Functional MRI Data Using a Brain Parcelling Technique
We present a comparison between a voxel based approach and a region based technique for detecting brain activation signals in sequences of functional Magnetic Resonance Images (fMR...
Guillaume Flandin, Ferath Kherif, Xavier Pennec, G...